Sasha wrote:
>On 4/12/06, Travis Oliphant <oliphant at ee.byu.edu> wrote:
>>>>... This also dove-tails nicely
>>with the Python 2.5 release schedule so that NumPy 1.0 should work with
>>Python 2.5 and be fully 64-bit capable for handling very-large arrays.
>>>>>>>>I would like to mention one feature that is going to appear in Python
>2.5 that is covering some of the functionality of NumPy. I am talking
>about the ctypes module
><http://starship.python.net/crew/theller/ctypes/tutorial.html>. Like
>NumPy, ctypes provides a set of python classes that represent basic C
>types:
>> c_byte
> c_char
> c_char_p
> c_double
> c_float
> c_int
> c_long
> c_short
> c_ubyte
> ...
>>and the ability to describe composite structures. The later
>functionality is very close to what dtype class provides in numpy.
>>There are some features in ctype that I like better than similar
>features in numpy. For example, in ctypes a fixed width array is
>described by multiplying basic type by an integer:
>>>>>>c_char * 10
>>>>>>>>><class '__main__.c_char_Array_10'>
>>I find this approach more elegant than numpy's dtype('S10').
>>It looks like there is some synergy to be exploited here, particularly
>in the area of record arrays.
>>
Definitely. I'm not familiar enough with c_types to do this. Any help
is appreciated.
-Travis